Introduction to the first international workshop on process management for highly dynamic and pervasive scenarios(PM4HDPS 2008)

Nowadays, process management systems (PMSs) are widely used in many business scenarios, e.g. by government agencies, by insurance companies, and by banks. Despite this widespread usage, the typical application of such systems is predominantly in the context of static scenarios, instead of pervasive and highly dynamic scenarios. Nevertheless, pervasive and highly dynamic scenarios could also benefit from the use of PMSs.

Informing engineering education for sustainable development using a deliberative dynamic model for curriculum renewal

Literature from around the world clearly suggests that engineering education has been relatively slow to incorporate significant knowledge and skill areas, including the rapidly emerging area of sustainable development. Within this context, this paper presents the findings of research that questioned how engineering educators could consistently implement systematic and intentional curriculum renewal that is responsive to emerging engineering challenges and opportunities. The paper presents a number of elements of systematic and intentional curriculum renewal that have been empirically distilled from a qualitative multiple-method iterative research approach including literature review, narrative enquiry, pilot trials and peer-review workshops undertaken by the authors with engineering educators from around the world. The paper also presents new knowledge arising from the research, in the form of a new model that demonstrates a dynamic and deliberative mechanism for strategically accelerating for curriculum renewal efforts. Specifically the paper discusses implications of this model to achieve education for sustainable development, across all disciplines of engineering. It concludes with broader research and practice implications for the field of education research.

Integrated approach for diagnostics and prognostics of HP LNG pump based on health state probability estimation

Effective machine fault prognostic technologies can lead to elimination of unscheduled downtime and increase machine useful life and consequently lead to reduction of maintenance costs as well as prevention of human casualties in real engineering asset management. This paper presents a technique for accurate assessment of the remnant life of machines based on health state probability estimation technique and historical failure knowledge embedded in the closed loop diagnostic and prognostic system. To estimate a discrete machine degradation state which can represent the complex nature of machine degradation effectively, the proposed prognostic model employed a classification algorithm which can use a number of damage sensitive features compared to conventional time series analysis techniques for accurate long-term prediction. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for the comparison of intelligent diagnostic test using five different classification algorithms. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state probability using the Support Vector Machine (SVM) classifier. The results obtained were very encouraging and showed that the proposed prognostics system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

Practical aspects of frequency-domain identification of dynamic models of marine structures from hydrodynamic data

The motion response of marine structures in waves can be studied using finite-dimensional linear-time-invariant approximating models. These models, obtained using system identification with data computed by hydrodynamic codes, find application in offshore training simulators, hardware-in-the-loop simulators for positioning control testing, and also in initial designs of wave-energy conversion devices. Different proposals have appeared in the literature to address the identification problem in both time and frequency domains, and recent work has highlighted the superiority of the frequency-domain methods. This paper summarises practical frequency-domain estimation algorithms that use constraints on model structure and parameters to refine the search of approximating parametric models. Practical issues associated with the identification are discussed, including the influence of radiation model accuracy in force-to-motion models, which are usually the ultimate modelling objective. The illustration examples in the paper are obtained using a freely available MATLAB toolbox developed by the authors, which implements the estimation algorithms described.

Hypergraph-based modeling of ad-hoc business processes

Process models are usually depicted as directed graphs, with nodes representing activities and directed edges control flow. While structured processes with pre-defined control flow have been studied in detail, flexible processes including ad-hoc activities need further investigation. This paper presents flexible process graph, a novel approach to model processes in the context of dynamic environment and adaptive process participants’ behavior. The approach allows defining execution constraints, which are more restrictive than traditional ad-hoc processes and less restrictive than traditional control flow, thereby balancing structured control flow with unstructured ad-hoc activities. Flexible process graph focuses on what can be done to perform a process. Process participants’ routing decisions are based on the current process state. As a formal grounding, the approach uses hypergraphs, where each edge can associate any number of nodes. Hypergraphs are used to define execution semantics of processes formally. We provide a process scenario to motivate and illustrate the approach.

Constrained predictive control of ship fin stabilizers to prevent dynamic stall

In moderate to high sea states, the effectiveness of ship fin stabilizers can severely deteriorate due to nonlinear effects arising from unsteady hydrodynamic characteristics of the fins: dynamic stall. These nonlinear effects take the form of a hysteresis, and they become very significant when the effective angle of attack of the fins exceeds a certain threshold angle. Dynamic stall can result in a complete loss of control action depending on how much the fins exceed the threshold angle. When this is detected, it is common to reduce the gain of the controller that commands the fins. This approach is cautious and tends to reduce performance when the conditions leading to dynamic stall disappear. An alternative approach for preventing the effects while keeping high performance, consists of estimating the effective angle of attack and set a conservative constraint on it as part of the control objectives. In this paper, we investigate the latter approach, and propose the use of a model predictive control (MPC) to prevent the development of these nonlinear effects by considering constraints on both the mechanical angle of the fins and the effective angle of attack.

On optimal control of constrained linear systems with imperfect state information and stochastic disturbances

We address the problem of finite horizon optimal control of discrete-time linear systems with input constraints and uncertainty. The uncertainty for the problem analysed is related to incomplete state information (output feedback) and stochastic disturbances. We analyse the complexities associated with finding optimal solutions. We also consider two suboptimal strategies that could be employed for larger optimization horizons.

Metabolic dysfunction and laminitis

Objective: This review focuses on laminitis that develops as a result of metabolic dysfunction and aims to provide a concise assessment of the current state of knowledge on this form of the disease. Outline: The most prevalent form of laminitis is associated with metabolic or endocrinopathic diseases, such as Equine Metabolic Syndrome and pituitary pars intermedia dysfunction, and the feeding of high-energy diets, particularly those rich in non-structural carbohydrates. Insulin dysregulation is the key hormonal imbalance implicated in causing this form of laminitis and hyperinsulinaemia is an important risk factor for the disease. Hyperinsulinaemia can occur in association with insulin resistance, obesity, regionalised adiposity, dysregulated cortisol metabolism and may also be related to other factors, such as breed and genetic predisposition. Recognition of hyperinsulinaemia is best achieved by using a dynamic oral glucose test that can be performed relatively easily under field conditions. Insulin produces a unique pathological lesion in the lamellae and the features of this lesion have informed investigations on the pathogenesis of the disease. Research into the mechanism of disease is continuing so that more targeted therapies than are currently available can be developed. However, dietary restriction and exercise remain effective management strategies for metabolic disease. Conclusions: Although the pathogenic mechanism/s of metabolic and endocrinopathic forms of laminitis remain the subject of intense research, ample data on risk factors for the disease are available. Efforts focussed on preventing the disease should aim to identify metabolic disease and reduce obesity and insulin resistance in at-risk individuals.

Regulation and integral control of an underactuated robotic system using IDA-PBC with dynamic extension

This paper proposes a method for design of a set-point regulation controller with integral action for an underactuated robotic system. The robot is described as a port-Hamiltonian system, and the control design is based on a coordinate transformation and a dynamic extension. Both the change of coordinates and the dynamic extension add extra degrees of freedom that facilitate the solution of the matching equation associated with interconnection and damping assignment passivity-based control designs (IDA-PBC). The stability of the controlled system is proved using the closed loop Hamiltonian as a Lyapunov candidate function. The performance of the proposed controller is shown in simulation.

Study on dynamic system optimum assignment to establish marginal time equilibrium

Several analytical methods for Dynamic System Optimum (DSO) assignment have been proposed but they are basically classified into two kinds. This chapter attempts to establish DSO by equilbrating the path dynamic marginal time (DMT). The authors analyze the path DMT for a single path with tandem bottlenecks and showed that the path DMT is not the simple summation of DMT associated with each bottleneck along the path. Next, the authors examined the DMT of several paths passing through a common bottleneck. It is shown that the externality at the bottleneck is shared by the paths in proportion to their demand from the current time until the queue vanishes. This share of the externality is caused by the departure rate shift under first in first out (FIFO) and the externality propagates to the downstream bottlenecks. However, the externalities propagates to the downstream are calculated out if downstream bottlenecks exist. Therefore, the authors concluded that the path DMT can be evaluated without considering the propagation of the externalities, but just as in the evaluation of the path DMT for a single path passing through a series of bottlenecks between the origin and destination. Based on the DMT analysis, the authors finally proposed a heuristic solution algorithm and verified it by comparing the numerical solution with the analytical one.

Numerical investigation of mechanical and thermal dynamic properties of the industrial transformer

Industrial transformer is one of the most critical assets in the power and heavy industry. Failures of transformers can cause enormous losses. The poor joints of the electrical circuit on transformers can cause overheating and results in stress concentration on the structure which is the major cause of catastrophic failure. Few researches have been focused on the mechanical properties of industrial transformers under overheating thermal conditions. In this paper, both mechanical and thermal properties of industrial transformers are jointly investigated using Finite Element Analysis (FEA). Dynamic response analysis is conducted on a modified transformer FEA model, and the computational results are compared with experimental results from literature to validate this simulation model. Based on the FEA model, thermal stress is calculated under different temperature conditions. These analysis results can provide insights to the understanding of the failure of transformers due to overheating, therefore are significant to assess winding fault, especially to the manufacturing and maintenance of large transformers.

A meshfree-based local Galerkin method with condensation of degree of freedom for elastic dynamic analysis

Condensation technique of degree of freedom is first proposed to improve the computational efficiency of meshfree method with Galerkin weak form for elastic dynamic analysis. In the present method, scattered nodes without connectivity are divided into several subsets by cells with arbitrary shape. Local discrete equation is established over each cell by using moving Kriging interpolation, in which the nodes that located in the cell are used for approximation. Then local discrete equations can be simplified by condensation of degree of freedom, which transfers equations of inner nodes to equations of boundary nodes based on cells. The global dynamic system equations are obtained by assembling all local discrete equations and are solved by using the standard implicit Newmark’s time integration scheme. In the scheme of present method, the calculation of each cell is carried out by meshfree method, and local search is implemented in interpolation. Numerical examples show that the present method has high computational efficiency and good accuracy in solving elastic dynamic problems.

Dynamic changes in high and low mammographic density human breast tissues maintained in murine tissue engineering chambers during various murine peripartum states and over time

Mammographic density (MD) is a strong heritable risk factor for breast cancer, and may decrease with increasing parity. However, the biomolecular basis for MD-associated breast cancer remains unclear, and systemic hormonal effects on MD-associated risk is poorly understood. This study assessed the effect of murine peripartum states on high and low MD tissue maintained in a xenograft model of human MD. Method High and low MD human breast tissues were precisely sampled under radiographic guidance from prophylactic mastectomy specimens of women. The high and low MD tissues were maintained in separate vascularised biochambers in nulliparous or pregnant SCID mice for 4 weeks, or mice undergoing postpartum involution or lactation for three additional weeks. High and low MD biochamber material was harvested for histologic and radiographic comparisons during various murine peripartum states. High and low MD biochamber tissues in nulliparous mice were harvested at different timepoints for histologic and radiographic comparisons. Results High MD biochamber tissues had decreased stromal (p = 0.0027), increased adipose (p = 0.0003) and a trend to increased glandular tissue areas (p = 0.076) after murine postpartum involution. Stromal areas decreased (p = 0.042), while glandular (p = 0.001) and adipose areas (p = 0.009) increased in high MD biochamber tissues during lactation. A difference in radiographic density was observed in high (p = 0.0021) or low MD biochamber tissues (p = 0.004) between nulliparous, pregnant and involution groups. No differences in tissue composition were observed in high or low MD biochamber tissues maintained for different durations, although radiographic density increased over time. Conclusion High MD biochamber tissues had measurable histologic changes after postpartum involution or lactation. Alterations in radiographic density occurred in biochamber tissues between different peripartum states and over time. These findings demonstrate the dynamic nature of the human MD xenograft model, providing a platform for studying the biomolecular basis of MD-associated cancer risk. © 2013 Springer Science+Business Media New York.

In the shadow of the welfare state : the role of payday lending in poverty survival in Australia

A defining characteristic of contemporary welfare governance in many western countries has been a reduced role for governments in direct provision of welfare, including housing, education, health and income support. One of the unintended consequences of devolutionary trends in social welfare is the development of a ‘shadow welfare state’ (Fairbanks, 2009; Gottschalk, 2000), which is a term used to describe the complex partnerships between statebased social protection, voluntarism and marketised forms of welfare. Coupled with this development, conditional workfare schemes in countries such as the United States, Canada, the UK and Australia are pushing more people into informal and semi-formal means of poverty survival (Karger, 2005). These transformations are actively reshaping welfare subjectivities and the role of the state in urban governance. Like other countries such as the US, Canada and the UK, the fringe lending sector in Australia has experienced considerable growth over the last decade. Large numbers of people on low incomes in Australia are turning to non-mainstream financial services, such as payday lenders, for the provision of credit to make ends meet. In this paper, we argue that the use of fringe lenders by people on low incomes reveals important theoretical and practical insights into the relationship between the mixed economy of welfare and the mixed economy of credit in poverty survival.

Freedom to choose? Embryo selection, reproductive decision-making and the role of the state

Involving the biopsy of an eight-cell embryo, PGD has been hailed as a means of making reproductive decisions without having to face the heart-wrenching decision to abort an affected foetus. However, controversy around the kinds of traits for which testing can be done, and who has access to the technology, has led to questions about the way in which the technology is developing. Women who are allowed to access in vitro fertilisation (IVF) services can currently also access PGD in limited circumstances.